An Introduction to the R-Statistical Software for Biologists
Presented by DJ Ko, Dan Polhamus, and Niki Stovall
Hosted by
UTSA Specialized Neuroscience Research Program
UTSA Neurosciences Institute
Dept of Management Science and Statistics
This workshop is free and open to the students and faculty in biology and statistics.
Date: January 16 and 23, 2009
Time: 9:00 am - 1:00 pm
Place: Business Building (BB) 3.02.18 (Stat. Lab.)
Maximum number of participants: 30
Advanced registration is required. To register, please email Salma.Quraishi@utsa.edu
R is the most widely used statistical software that can be freely downloaded
(http://www.r-project.org). It has revolutionized statistical data analysis for most
bioscience disciplines. The time required to learn R software is well invested, since the
R environment covers an unmatched spectrum of statistical tools, including an efficient
programming language for automating time-consuming analysis routines. Due to its
popularity, R is continuously updated and extended with the latest analysis tools
available in various research fields. This workshop provides an elementary-level
introduction into the R environment covering the following topics: (1) command syntax,
(2) basic functions, (3) data import/export, (4) data types, (5) using R for data mining, (6)
graphical display and (7) usage of R packages and libraries (e.g. Spike Train Analysis in
R).
This workshop is ideal for graduate students and researchers in biology and applied
statistics.
Agenda
1. R Basics
A. Introduction
B. Finding Help
C. Basics on Functions and Packages
D. System commands under Linux
E. Reading and Writing External Data
F. R Objects
G. Some Great R Functions
H. Graphical Procedures
I. Missing Values
J. Writing Your Own Functions
K. R Web Applications
L. R Exercises
2.
Programming in R
A. Control Structures
B. Functions
C. Useful Utilities
D. Running R Programs
E. Object-Oriented Programming
F. Exercises